Get a comprehensive view of all the training sessions scheduled for the year with our Training Calendar. Now plan your training schedule and choose from a range of courses at your convenience.
Our calendar makes it easier for you to choose from our diverse range of courses. The calendar includes different types of courses, such as one-day sessions & boot camps, enterprise training, and certification courses. Not only do you get a clear picture of what courses are available, but you can also choose courses that best suit your schedule.
Building Agentic AI with Amazon Bedrock AgentCore is an intermediate, 1-day instructor-led AWS classroom training designed to help learners move agentic AI systems from experimentation to enterprise-grade production.
Participants explore agentic AI patterns, understand core agent components and their interactions, and implement production-ready architectures using Amazon Bedrock AgentCore capabilities such as Runtime, Identity, Policy, Gateway, Memory, Observability, and Evaluations.
The course combines presentations, hands-on labs, and group exercises to ensure learners can confidently design, secure, deploy, and monitor agentic AI systems in real-world environments.
Building Advanced Agentic Systems on AWS is a 1‑day advanced-level AWS classroom training designed for developers and technical teams ready to build real-world, production-grade multi-agent systems.
The course covers multi-agent communication patterns, context engineering, security controls, VPC integration, policy-based access, observability, distributed tracing, and evaluation frameworks. Hands-on labs and instructor demonstrations help learners design and deploy scalable agent architectures using Amazon Bedrock AgentCore.
This comprehensive course provides an end-to-end learning journey into the design, implementation, and governance of generative AI systems using AWS services. Participants will explore advanced concepts such as dynamic model selection, resilient deployment patterns, and cross-region reliability strategies. You’ll learn to build vector search and retrieval systems, develop prompt engineering and agent orchestration frameworks, and enforce AI safety, security, and observability controls. The course also emphasizes performance optimization, cost management, and continuous testing methodologies, equipping learners with the skills to deliver secure, compliant, and scalable AI architectures in production environments.
The Data Engineering on AWS course is designed for data professionals who want to learn how to design, build, secure, and optimize data pipelines on AWS. Through a combination of lectures, demonstrations, and hands-on labs, participants will gain practical experience in ingesting, transforming, storing, and analyzing data using AWS data services.
This course covers essential data engineering topics such as data lakes, batch and streaming data processing, orchestration, and automation, enabling learners to create scalable, efficient, and secure data pipelines aligned with AWS best practices.
By the end of this course, learners will have the skills to design and implement data workflows for real-world analytics and machine learning applications.
This course is designed specifically for business users and decision-makers seeking a foundational understanding of generative AI. It covers the distinction between generative AI and other forms of AI, introduces key personas and use cases, and explores the ethical dimensions of responsible AI. Through interactive lectures and case study analysis, the course inspires leaders to explore how generative AI can create impact across business functions using Google Cloud technologies such as Vertex AI and Gemini.
This 1-day, fundamental-level training introduces participants to the principles, components, and AWS services that power Agentic AI. You’ll explore how agentic systems differ from traditional conversational AI, learn workflows, autonomous agents, hybrid architectures, and gain hands-on experience building goal-driven AI solutions with Amazon Bedrock Agents and AgentCore.
This Cloud Operations on AWS course is ideal for systems operators and anyone wanting to learn how to deploy, manage, and operate workloads on AWS. In addition, by attending this Cloud Operations on AWS training, candidates also learn how to automate, secure, monitor, maintain and troubleshoot networks, systems, and services running on AWS to support business applications.
The Cloud Operations on AWS course also offers candidates an understanding of specific AWS features, tools, and best practices related to these functions. This Course includes instructor presentations, hands-on labs, demonstrations, and group knowledge checks.
This training is designed to prepare learners for the Machine Learning Engineering on AWS. It focuses on developing end-to-end ML solutions on AWS. Learners will explore problem framing, data engineering, model training and evaluation, deployment, monitoring, and optimization. Through hands-on labs, real-world scenarios, and exam-focused guidance, students will gain practical ML skills and a thorough understanding of AWS services like SageMaker, S3, Glue, and CloudWatch.
This one-day training course offers a comprehensive introduction to generative AI using AWS services. Participants will explore key concepts, practical use cases, and hands-on labs to optimize AI model performance. The course emphasizes responsible AI principles, security, governance, and compliance, ensuring ethical AI practices. Through real-world demos and a capstone project, attendees will gain the skills needed to implement generative AI projects and integrate them into the development lifecycle. Ideal for career advancement in AI, the course provides networking opportunities and post-training support.
The AWS Cloud Practitioner Essentials covers the following domains:
Cloud Concepts: This domain assesses your understanding of the fundamental aspects of cloud computing and how AWS implements these concepts. It covers topics such as the advantages of using the AWS Cloud, the different types of cloud computing, and the basic global infrastructure of AWS.
Security and Compliance: This domain evaluates your understanding of AWS security and compliance concepts and the shared responsibility model. It covers topics such as the AWS shared responsibility model, AWS security and compliance concepts, and the AWS access management capabilities.
Technology: This domain examines your understanding of AWS Cloud services and their use cases. It covers topics such as the different AWS service categories, key AWS services, and their common use cases.
Billing and Pricing: This domain assesses your understanding of AWS billing, account management, and pricing models. It covers topics such as the fundamentals of AWS billing, pricing models for various AWS services, and account management best practices.
Do you want generative AI to enhance customer experiences and resolve challenging business issues? Developing Generative AI Applications on AWS teaches you how to create generative AI applications.
During this two-day course, a knowledgeable instructor with experience in Python will walk you through the fundamentals, advantages, and related jargon of generative artificial intelligence as a developer. In order to create generative AI applications using AWS services, you will discover the fundamentals of prompt engineering, how to plan a generative AI project, and more. By the end of the course, you will acquire the knowledge and abilities required to create applications that can answer queries, create and summarize text, and communicate with users via a chatbot interface.
AWS Security Essentials is fundamental-level 1-day course covers fundamental security concepts on AWS Cloud. This course covers AWS access control, data encryption methods, and how to secure the network access to your AWS infrastructure. Learners get to understand AWS Shared Responsibility Model which divides the responsibility of security of the cloud and security in the cloud amongst AWS and customers respectively. Security needs of an organization implemented as Security-oriented services available in AWS will be the highlight of this training.
The MLOps Engineering on AWS course is designed to provide hands-on experience and knowledge in building, training, deploying, monitoring, and managing machine learning models on AWS. The course will guide you through setting up the environment, designing ML pipelines, and implementing the best practices to ensure high-performing and scalable solutions.
Introduction to MLOps on AWS: Understanding the key concepts and principles of MLOps and its importance in the machine learning lifecycle. Exploring the AWS ecosystem for MLOps, including Amazon SageMaker, AWS Lambda, Amazon S3, AWS Batch, and more.
Building and Deploying Machine Learning Models on AWS: Designing and implementing end-to-end machine learning pipelines on AWS. This includes data preprocessing, model training, model evaluation, and model deployment using Amazon SageMaker and other AWS services.
Monitoring and Managing Machine Learning Models on AWS: Monitoring machine learning models in production using Amazon CloudWatch and other AWS monitoring tools. Understanding best practices for managing and scaling machine learning infrastructure on AWS.
Optimizing and Scaling Machine Learning Workloads on AWS: Troubleshooting and optimizing machine learning pipelines for performance and scalability. Exploring strategies for automating and scaling machine learning workloads using AWS Batch, AWS Lambda, and other AWS services.
Introduction to Amazon SageMaker Studio: An overview of SageMaker Studio’s features, including its integrated Jupyter notebooks, model debugging, and experimentation tools.
Data Preprocessing: Techniques for preparing and cleaning datasets for training and inference.
Model Building and Training: How to build and train machine learning models using SageMaker’s built-in algorithms and AutoML capabilities.
Model Deployment and Monitoring: Deploying models to SageMaker endpoints and monitoring their performance.
Continuous Integration/Continuous Deployment (CI/CD) Pipelines: Automating the process of deploying and updating models in production.
This course will teach you how to use Amazon EMR, an enterprise-grade managed service for Apache Spark and Apache Hadoop, to create batch data analytics solutions. You will discover how AWS services such as AWS Glue and AWS Lake Formation, as well as open-source initiatives such as Apache Hive, Hue, and HBase, are integrated with Amazon EMR. In the context of Spark and Hadoop, the course covers data ingestion, cataloging, storage, and processing. You will gain knowledge on how to support workloads related to machine learning and analytics using EMR Notebooks. Additionally, you will learn best practices for cost management, performance, and security when using Amazon EMR.
Building Data Analytics Solutions using Amazon Redshift
This course guides you through creating an end-to-end analytics solution using Amazon Redshift, a managed cloud-based data warehouse. It covers the complete data lifecycle—from gathering and ingesting data to organizing, storing, and transforming it for analysis. You will also learn how to integrate Redshift with a data lake to support advanced analytics and machine learning scenarios. Along the way, the course highlights practical approaches to ensure data security, improve system performance, and manage costs effectively.
Building Streaming Data Analytics Solutions on AWS
Through a combination of instructor-led presentations, practice labs, demonstrations, and in-class exercises, the course delves deeply into Amazon Kinesis and Amazon MSK so that you can leave with an understanding of how to create a streaming data analytics solution on AWS. Along with these skills, you’ll learn how to use Amazon Kinesis and Amazon MSK to scale streaming applications, optimize data storage, choose and implement the best options for ingesting, transforming, storing, and analyzing data.
The Architecting on AWS Course teaches candidates about the fundamentals of building IT infrastructure on the AWS platform. Candidates attending this Architecting on AWS training to learn how to optimize the AWS Cloud and how to use the AWS to fit into cloud-based solutions.
The Architecting on AWS training covers best practices and design patterns to help candidates to learn how to architect optimal IT solutions on the AWS Cloud and build and explore a variety of infrastructures through guided discussions and hands-on activity. The course comprises presentations, group exercises, and hands-on labs.
Exam PL-900: Introduction to Microsoft Power Platform
PL-900 exam measures your ability to describe the business value of Power Platform; identify the core components of Power Platform; demonstrate the capabilities of Power BI; describe the capabilities of Power Apps; demonstrate the capabilities of Power Automate; and demonstrate the business value of Power Virtual Agents.
PL-600: Microsoft Power Platform Solution Architect
The PL-600 Microsoft Power Platform Solution Architect training course from CloudThat is ideal for solution architects having technical and functional knowledge of Dynamics 365 customer engagement apps, such as Microsoft cloud solutions, Power Platform, and third-party technologies. Candidates for this PL-600 exam lead successful implementations and focus on building solutions that address organizations’ business and technical needs.
Candidates attending this Microsoft Power Platform Solution Architect training perform proactive and preventative tasks to promote organizational health and design decisions across development, configuration, integration, security, infrastructure, availability, licensing, storage, and change management.
PL-300: Design and manage analytics solutions using Power BI
PL-300 is a Microsoft certification exam focusing on the tool Power BI, including designing solutions, creating solutions, implementing solutions, and supporting organizational adoption of the Power Platform.
The Microsoft PL-300 Power BI course is structured to provide instruction on utilizing Power BI, a business intelligence tool that empowers users to analyze and visualize data from diverse sources. PL-300 power bi course covers the following topics:
Introduction to Power BI: This section provides an overview of Power BI, including its capabilities, architecture, and data sources.
Connecting to Data: This section covers how to establish connections with diverse data sources, such as Excel, SQL Server, and cloud-based data sources.
Data Modeling: Learn to create relationships between tables, develop calculated columns and measures, and build hierarchies.
Visualizations: Discover how to create and customize visualizations, such as tables, charts, maps, and gauges.
Dashboards and Reports: Understand how to create dashboards and reports to meaningfully visualize data and share it with others.
Publishing and Sharing: Learn to publish and share dashboards and reports within your organization.
Power BI Service: Explore the Power BI service, including accessing it, working in workspaces, and collaborating.
The PL 300 certification course typically includes hands-on labs and exercises to reinforce your learning. Upon completing the course, you will have a solid understanding of Power BI, enabling you to create visualizations, dashboards, and reports that provide valuable insights from data.
Microsoft Power BI Data Analyst-Exam Details (PL 300)
Certification Name
Microsoft Certified: Power BI Data Analyst Associate
Question Type
Multiple-choice and Multiple response questions
Exam Cost
USD 165.00*
Total Questions
40 – 60 Questions
Exam Duration
100 minutes (to answer the questions)
PL-200: Microsoft Power Platform Functional Consultant
In PL-200 Power Platform Functional Consultant certification training course from CloudThat, students will learn to perform discovery, capture requirements, engage subject matter experts and stakeholders, translate requirements, and configure Power Platform solutions and apps. They will supplement their learnings with hands-on labs to create application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and custom visualizations. The Power Platform empowers organizations to automate business processes, develop their own rich app experiences, and connect with customers better and faster.
AZ-305: Designing Microsoft Azure Infrastructure Solution
Candidates for this AZ-305 Exam should have advanced experience and knowledge of IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platforms, and governance. A professional in this role should manage how decisions in each area affect an overall solution. In addition, they should have experience in Azure administration, Azure development, and DevOps processes.
This AZ-500 certification training course from CloudThat is designed to train IT professionals who plan to take the Microsoft AZ-500 certification exam. This course and passing the AZ-500 exam will meet all the requirements to become a Microsoft Certified Azure Security Engineer Associate.
The Microsoft Certified Azure Security Engineer Associate certification offers in-depth knowledge and understanding of Azure Security Technologies.
Azure security engineers often serve as part of a larger team to plan and implement cloud-based management and security. The responsibilities of an Azure security engineer include managing the security posture, identifying and remediating vulnerabilities, performing threat modeling, implementing threat protection, and responding to security incident escalations.
SC-100: Microsoft Cybersecurity Architect Training Course
The Microsoft Cybersecurity Architect certification training from CloudThat has been designed for candidates for SC-100 training to become a Microsoft certified Cybersecurity Architect Expert. This course teaches candidates; how to design a Zero Trust strategy and architecture; evaluate Governance Risk Compliance (GRC) technical strategies and security operations strategies; design security for infrastructure; and design a strategy for data and applications.
The Microsoft cybersecurity architect has subject matter expertise in designing and evolving the cybersecurity strategy to protect an organization’s mission and business processes across all aspects of the enterprise architecture. The cybersecurity architect continuously collaborates with leaders and practitioners in IT security, privacy, and other roles across an organization to plan and implement a cybersecurity strategy that meets the business needs of an organization.
AI-102: AI-102 equips you with the expertise to design, develop, and implement AI solutions using Azure AI. This course integrates your existing programming and AI knowledge to manage AI solution planning, image and video processing, natural language processing, knowledge mining, and conversational AI implementation.
SC-300: Microsoft Identity and Access Administrator
This Microsoft Identity and Access Administrator certification training course from CloudThat teaches candidates how to design, implement, and operate an organization’s identity and access management systems using Azure Active Directory (Azure AD). Candidates taking up this Azure SC-300 course also learn how to secure authentication and authorization access to enterprise applications and provide seamless experiences and self-service management capabilities to all users. An Identity and Access Administrator Associate is also responsible for monitoring, troubleshooting, and reporting on the identity and access environment.
This Microsoft Security Operations Analyst certification training from CloudThat teaches candidates how to mitigate threats using Microsoft 365 Defender, Microsoft Defender for Cloud, and Microsoft Sentinel. Candidates taking up course SC-200 also learn to secure information technology systems, reduce organizational risk, advise best practices for threat protection, and refer violations of organizational policies to stakeholders.
The responsibilities of Azure Security Operations Analyst include threat management, response, and monitoring, using a variety of security solutions. They also use Azure Defender, Microsoft Azure Sentinel, Microsoft 365 Defender, and third-party security products to investigate, respond, and identify threats.
Advanced Architecting on AWS training explores available AWS services and features as solutions to the problem. It helps you to gain insights by participating in problem-based discussions and learning about the AWS services that you could apply to meet the challenges. Over three days, this Advanced Architecting on AWS training goes beyond the basics of cloud infrastructure and covers topics to meet a variety of needs for AWS customers.
Course modules focus on managing multiple AWS accounts, hybrid connectivity, networking with a focus on AWS Transit Gateway connectivity, container services, automation tools for continuous integration/continuous delivery (CI/CD), security and distributed denial of service (DDoS) protection, data lakes and data stores, edge services, migration options, and managing costs. Advanced Architecting on AWS concludes by presenting you with scenarios and challenges to identify the best solutions. This course includes presentations, group discussions, use-cases, assessments, and hands-on labs.
This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. It highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents. This course includes presentations, demonstrations, and hands-on labs.
This DevOps Engineering on AWS course teaches candidates how to use the combination of DevOps cultural philosophies, practices, and tools to increase the organization’s ability to develop, deliver, and maintain applications and services at high velocity on AWS.
This DevOps Engineering on AWS course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications.
The DevOps Engineering on AWS course comprises presentations, group exercises, and hands-on labs. In addition, labs for multi-pipeline workflows and pipelines deployed to multiple environments are also included.
The course content usually covers the following key topics:
Introduction to AWS: Overview of the AWS platform, its global infrastructure, and key service domains.
AWS Architecture: Understanding the basic architectural principles of AWS, including regions, availability zones, and edge locations.
Compute Services: Overview of various compute services offered by AWS, such as Amazon Elastic Compute Cloud (EC2) and AWS Lambda.
Storage Services: Introduction to different storage services, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), and Amazon Glacier.
Networking and Content Delivery: Basic networking concepts within AWS, including Amazon Virtual Private Cloud (VPC), Route 53, and CloudFront.
Databases on AWS: Overview of database services provided by AWS, including Amazon Relational Database Service (RDS) and Amazon DynamoDB.
Security and Identity Services: Introduction to the security and identity services available on AWS, such as AWS Identity and Access Management (IAM) and AWS Key Management Service (KMS).
AWS Management Tools: Overview of various management and monitoring tools, including AWS CloudTrail, AWS CloudWatch, and AWS Trusted Advisor.
The course is intended to provide a broad overview of the AWS platform and its key services, enabling participants to understand the basic building blocks of cloud architecture and how to use various AWS services effectively. It serves as a starting point for individuals looking to gain a foundational understanding of AWS and prepare for more advanced AWS courses.
Networking Essentials for Cloud Applications on AWS
The Networking Essentials for Cloud Applications on AWS course delivers a thorough introduction to networking within the AWS cloud. Tailored for both new and experienced networking professionals, it explores core concepts, recommended practices, and hands-on exercises. The course is designed to develop the expertise required to effectively design, implement, and optimize AWS-based network infrastructures.
AZ-801: Configuring Windows Server Hybrid Advanced Services
This Microsoft AZ-801 certification training course from CloudThat teaches candidates how to configure advanced Windows Server services using hybrid and on-premises cloud technologies. In addition, candidates also learn how to migrate servers and workloads, implement and manage Windows Server high availability, monitor and troubleshoot Windows Server environments, secure Windows Server on-premises and hybrid infrastructures and implement disaster recovery.
Candidates taking up this exam AZ-801 should have expertise in performing tasks related to migration, security, monitoring, troubleshooting, high availability, and disaster recovery. This training provides candidates with skills to use administrative tools and technologies, including Microsoft Defender for Identity, PowerShell, Azure Migrate, Azure Arc, Windows Admin Center, Azure Automation Update Management, and Azure Monitor.
AZ-800: Administering Windows Server Hybrid Core Infrastructure
CloudThat’s Microsoft AZ-800 certification training equips individuals with the skills to proficiently handle Windows Servers and workloads within a hybrid setting. It instructs on deploying and overseeing Active Directory Domain Services (AD DS) across on-premises and cloud environments, as well as managing virtual machines and containers. Moreover, this course provides insights into effective storage and file service management, along with the implementation and administration of on-premises and hybrid networking infrastructure.
The Windows Server Hybrid Administrator Associate certification comprises two distinct exams. The AZ-800 exam focuses on fundamental server administration duties, while the AZ-801 delves deeper into specialized tasks such as disaster recovery and workload migration. Achieving the Windows Server Hybrid Administrator Associate certification necessitates successfully passing both of these exams.
Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) Training
In this course, you will learn how to use Amazon EKS to manage and orchestrate containers with Kubernetes. With Amazon EKS you can run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. You will manage container images using Amazon Elastic Container Registry (Amazon ECR) and learn how to automate application deployment. You will deploy applications using continuous integration and delivery (CI/CD) tools. You will learn how to monitor and scale your environment by using metrics, logging, tracing, and horizontal and vertical scaling. You will also manage storage for your containerized applications, configure AWS networking services to support the cluster and learn how to secure your Amazon EKS environment.
Practical Data Science with Amazon SageMaker Training
In this Practical Data Science with Amazon Sagemaker certification training course, candidates learn to solve a real-world use case with Machine Learning (ML) using Amazon SageMaker. From analyzing and visualizing a dataset to preparing the data, and feature engineering, candidates taking up this Practical Data Science with Amazon Sagemaker course learn about the different stages of a typical data science process for Machine Learning.
By enrolling in this Practical Data Science with Amazon Sagemaker online course, candidates also learn about the practical aspects of model building, tuning, and deployment with Amazon SageMaker. Trainers use real-life use cases, group exercises, and hands-on labs to deliver engaging sessions on Amazon SageMaker.
The course content usually covers the following key topics:
Introduction to Serverless Computing: An overview of serverless architecture, its advantages, and its relevance in modern application development.
AWS Serverless Services: In-depth exploration of various AWS serverless services, including AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon S3, Amazon SNS, and Amazon SQS, along with their integration patterns.
Serverless Application Development with AWS Lambda: Practical guidance on writing, deploying, and managing AWS Lambda functions for executing code without the need to provision or manage servers.
Serverless Application Deployment Best Practices: Strategies for deploying serverless applications using AWS CloudFormation or other deployment tools to ensure scalability, security, and high availability.
Event-Driven Architectures: Implementation and understanding of event-driven architectures using AWS services, including how to trigger AWS Lambda functions in response to various events.
Serverless Application Security: Best practices for securing serverless applications, encompassing access control, encryption, and the implementation of security measures for data protection.
Monitoring and Debugging Serverless Applications: Techniques for monitoring and troubleshooting serverless applications using AWS CloudWatch, X-Ray, and other monitoring tools.
Best Practices and Optimization Techniques: Guidance on optimizing serverless applications, including performance tuning, cost optimization, and efficient resource management.
Real-World Use Cases: Exploration of real-world use cases and case studies that illustrate the practical application of serverless solutions on the AWS platform.
This course helps experienced developers build web applications by programmatically interacting with AWS services. It covers key architectural concepts, resource selection, and practical use of AWS SDKs and the CLI for development and deployment. You will create a sample application while learning to manage permissions, implement business logic, configure authentication, deploy to the cloud, and troubleshoot issues.
The course also includes code examples and hands-on labs using SDKs for Python, .NET, and Java, along with the AWS CLI and Management Console.
This course teaches the fundamentals and best practices for building a cloud-based data warehouse using Amazon Redshift. It covers how to collect, store, and process data efficiently while explaining Redshift’s features and its role in solving business and technical challenges. You will also learn solution design using the Well-Architected Framework, along with integration, performance optimization, orchestration, security, and monitoring.
Building Data Lakes on AWS helps learn how to build an operational data lake to analyze both structured and unstructured data. Taking up this training on building Data Lakes on AWS, candidates are trained to use the various components and features of AWS services to create a data lake.
This Building Data Lakes on AWS training teaches candidates how to use AWS Glue to build a data catalog, AWS Lake Formation to build a data lake, and Amazon Athena to analyze data. The course comprises presentations, lectures, hands-on labs, and group exercises.
This Migrating to AWS course from CloudThat offers candidates an understanding of how to plan and migrate existing workloads to the AWS Cloud. Candidates taking up this AWS Cloud Migration training to learn about various cloud migration strategies and how to conduct a migration, apply portfolio discovery, post-migration validation, application optimization, and application migration planning and design.
This Migrating to AWS course provides hands-on lab, learning sessions to provide candidates with an in-depth understanding about migration concepts and knowledge necessary to complete migration tasks. The course comprises presentations, demonstrations, assessments, and group exercises.
MB-910: Microsoft Dynamics 365 Fundamentals Customer Engagement Apps (CRM)
Note: This course is no longer available and has been officially retired. As an alternative, you may consider MB-230 or MB-280
This Microsoft Dynamics 365 Fundamentals Customer Engagement Apps (MB-910) certification training course from CloudThat is ideal for tech-savvy individuals having basic knowledge of business functions like sales, marketing, support lifecycles, and services. This exam MB-910 provides candidates fundamental understanding of customer engagement features and capabilities of Dynamics 365 apps.
Candidates taking up this MB-910 certification course are introduced to Dynamics 365 Sales, Dynamics 365 Marketing, Dynamics 365 Field Service, Dynamics 365 Customer Service, and shared features.
The DP-203: Data Engineering on Microsoft Azure course from CloudThat provides comprehensive training and study materials to help candidates prepare for the DP-203 certification exam. This course replaces the DP-200 and DP-201 exams, which retired on June 30, 2021.
Through this updated curriculum, learners gain the necessary skills to successfully clear the DP-203 exam and become certified Azure Data Engineers.
DP-100: Design & Implement Data Science Solution on Azure
The DP 100 certification provides you with the skills to implement machine learning solutions at cloud scale using Azure Machine Learning. This course is designed to integrate your existing Python and machine learning expertise, allowing you to effectively manage data ingestion and preparation, model training, deployment, and solution monitoring using Azure Machine Learning and MLflow.
At CloudThat, we have expert training consultants with years of experience and unique teaching methodologies. Our hands-on approach helps learners build practical skills, and our trainers are available to support the learners even after the course completion. With our Training Calendar, you have access to comprehensive training schedules and courses that can help you get ahead in your career.
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